ArticleTranslational vision science & technology2024
Characteristics of a Large Database of Healthy Eyes From Optometry Practices: Implications for a Real-World Reference Database.
Article in Translational vision science & technology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Larger Real-World OCT Reference Database Improves Accuracy of Glaucoma Flagging Using Summary Metrics.Translational vision science & technology · 2026Article
- A Deep Learning Model Detects Glaucoma Based on an OCT Report, but Where Should the Clinician Look to Identify Glaucomatous Damage?Translational vision science & technology · 2025Article
- A Deep Learning Model for Glaucoma Detection Outperforms Conventional Metrics.Translational vision science & technology · 2025Article
- A Pattern-Based OCT Metric for Glaucoma Detection.Translational vision science & technology · 2024Article
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Authors and funding
8 authors.
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Abstract
Purpose: To compare an optical coherence tomography (OCT) real-world reference database (RW-RDB) of "healthy" eyes obtained from optometry practices to a commercial reference database (RDB). Methods: OCT scans from 6804 individuals 18 years and older were sampled from a larger database tested at 10 optometry practices involved in refractive and screening services. Employing a reading center method, OCT scans from both eyes of 4932 (4.9K) individuals were judged to be of acceptable quality with an absence of pathology. The 4.9K RW-RDB was compared to a commercial RDB with 398 eyes (398 RDB). Results: The means and distributions of global circumpapillary retinal nerve fiber layer (G-cpRNFL) and global ganglion cell layer (G-GCL) thickness, as well as five key anatomical parameters affecting cpRNFL thickness, were not significantly different for all but one parameter (fovea-to-disc distance) and one thickness metric (G-cpRNFL). In both cases, the difference amounted to less than 1.5%. By design, the number of 4.9K RW-RDB eyes 70 years and older (724, 14.7%) was greater than for the 398 RDB (40, 10.1%). The error bands on the 5% and 1% quantile regression lines (QRLs) were substantially narrower for the 4.9K RW-RDB. Conclusions: The 398 RDB and 4.9K RW-RDB have similar characteristics and appear to come from a similar population. However, the large size of the 4.9K RW-RDB leads to narrower error bands of the QRLs, which has the potential to increase accuracy. Translational Relevance: The larger RW-RDB offers the opportunity to better characterize healthy eyes for clinical diagnosis and clinical trials by furthering our understanding of the patterns of artifacts, exploring covariates, developing separate RW-RDBs, and/or improving AI models.
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